# LakeSurvey.csv
#
# This is only a portion of the actual survey which can be found at
#   http://lter.limnology.wisc.edu/sites/default/files/ntl/pdf/nwlr_survey.pdf
#
# lake: lake that respondent lives on
# year: year that respondent bought their property
# prmryRes: whether or not the property is the respondent's primary residence
# sumDays: number of summer days the respondent (or their family) spends at the residence
# sumGuest: number of summer days that a guest spends at the residence
# sumRent: number of summer days that the residence is rented
# fishing: approx. days (as a category) that respondent spends fishing
# boating: approx. days (as a category) that respondent spends boating
# waterSki: approx. days (as a category) that respondent spends water skiing
# smallBoats: approx. days (as a category) that respondent spends in a canoe, kayak, or rowboat
# sail: approx. days (as a category) that respondent spends sailboating
# jetSki: approx. days (as a category) that respondent spends jet skiing
# swim: approx. days (as a category) that respondent spends swimming
# gender: the respondent's gender (male or female)
# age: the respondent's age
# sizeHousehold: number of members in the respondent's household
# children: number of children under age-18 in the household
# educat: categorical level of education (ltHS=no high school diploma,
#         HS= highschool diploma, someColl=some College, College= BA, BS,
#         or AA degree, GradProf=graduate or professional degree)
# inc: income category (30=30000-39999, 40-40000-49999, etc.)
# value: respondent's belief as to the current value of their property
#
# These data are often used for a final exam in Ogle's Intro Stats course. For
#  that course, run the following code after you have read the data into the
#  df object to make the data easier to manage.
#
#    use.levs <- c("0_days","1_6_days","7_14_days","15_30_days","30_60_days","60+_days")
#    edu.levs <- c("ltHS","HS","someColl","College","GradProf")
#
#    df <- dplyr::select(df,lake:sumDays,educat,fishing,age,value)
#    df$fishing <- factor(df$fishing,levels=use.levs)
#    df$educat <- factor(df$educat,levels=edu.levs)
#    df$prmryRes <- factor(df$prmryRes,levels=c("No","Yes"))
#